Bayesian fishery stock assessment and decision making using adaptive importance sampling

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 53, Issue 2, 1996, Pages 414-423

  Kinas, Paul Gerhard ^a  

^a Universidade Federai do Rio Grande   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ATLANTICUS; HOPLOSTETHUS ATLANTICUS;

BAYESIAN DECISION ANALYSIS; FISHERY MANAGEMENT; SAMPLING; STOCK ASSESSMENT;

EID: 0029730671     PISSN: 0706652X     EISSN: None     Source Type: Journal    
DOI: 10.1139/f95-189     Document Type: Article

References (27)

1. Abramowich, M., and Stegun, I.A. 1964. Handbook of mathematical functions. National Bureau of Standards, Washington, D.C.
2. Berger, O.J. 1985. Statistical decision theory and bayesian analysis. Springer Verlag, New York.
3. Efron, B. 1982. The jacknife, the bootstrap and other resampling plans. SIAM-CBMS, 38: 1-92.
4. Francis, R.I.C.C. 1993. The interpretation of "probability": a response to Walters comment. Can. J. Fish. Aquat. Sci. 50: 882-883.
5. Geweke, J. 1989. Bayesian inference in econometric models using Monte Carlo integration. Econometrica, 57: 1377-1339.
6. Givens, G.H., Raftery, A.E., and Zeh, J.E. 1993. Benefits of a Bayesian approach for synthesizing multiple sources of evidence and uncertainty linked by a deterministic model. Rep. Int. Whal. Comm. 43: 495-500.
7. Givens, G.H., Raftery, A.E., and Zen, I.E. 1994. A reweighting approach for sensitivity analysis within the Bayesian synthesis framework for population assessment modeling. Rep. Int. Whal. Comm. 44: 377-383.
8. Hilborn, R., Pikitch, E.K., and Francis, R.C. 1993a. Current trends in including risk and uncertainty in stock assessment and harvest decisions. Can. J. Fish. Aquat. Sci. 50: 874-880.
9. Hilborn, R., Pikitch, E.K., McAllister, M.M., and Punt, A. 1993b. A comment on "Use of risk analysis to assess fishery management strategies: a case study using orange roughy (Hoplostethus atlanticus) on the Chatham Rise, New Zealand" by R.I.C.C. Francis. Can. J. Fish. Aquat. Sci. 50: 1122-1125.
10. Jeffreys, H. 1961. Theory of probability. 3rd ed. Oxford University Press, London.
11. Johnson, N.L., and Kotz, S. 1970. Continuous univariate distributions. Houghton Mifflin, Boston.
12. Kinas, P.G. 1993. Bayesian statistics for fishery stock assessment and management. Ph.D. thesis, Department of Statistics, University of British Columbia, Vancouver, B.C.
13. Kloek, T., and van Dijk, H.K. 1978. Bayesian estimates of equation system parameters: an application of integration by Monte Carlo. Econometrica, 46: 1-19.
14. Ludwig, D., and Walters, C.J. 1985. Are age structured models appropriate for catch-effort data? Can. J. Fish. Aquat. Sci. 42: 1066-1072.
15. Ludwig, D., and Walters, C.J. 1989. A robust method for parameter estimation from catch and effort data. Can. J. Fish. Aquat. Sci. 46: 137-144.
16. Naylor, J.C., and Smith, A.F.M. 1988. Econometric illustrations of novel numerical integration strategies for Bayesian inference. J. Econometrics, 38: 103-125.
17. Pella, J.J., and Tomlinson, P.K. 1969. A generalized stock-production model. Bull. Int.-Am. Trop. Tuna Comm. 13: 419-496.
18. Ripley, B. 1987. Stochastic simulation. John Wiley & Sons, New York.
19. Rubin, D.B. 1988. Using the SIR algorithm to simulate posterior distributions. In Bayesian Statistics 3: Proceedings of the Third Valencia International Meeting, Valencia, Spain. Edited by J.M. Bernardo, M.H. DeGroot, D.V. Lindley, and A.F.M. Smith. Clarendon Press, Oxford.
20. Silverman, B.W. 1986. Density estimation for statistics and data analysis. Chapman and Hall, London.
21. Smith, A.F.M. 1991. Bayesian computational methods. Philos. Trans. R. Soc. Lond. A Math. Phys. Sci. 337: 369-386.
22. Smith, A.F.M., and Gelfand, A.E. 1992. Bayesian statistics without tears: a sampling-resampling perspective. Am. Stat. 46: 84-88.
23. Walters, C.J. 1986. Adaptive management of renewable resources. McMillan Publishing Co., New York.
24. Walters, C.J. 1993. Comment on R.I.C.C. Francis: computing probability distributions for risk analysis. Can. J. Fish. Aquat. Sci. 50: 881-882.
25. West, M. 1992. Modelling with mixtures. In Bayesian Statistics 4: Proceedings of the Fourth Valencia International Meeting, Valencia, Spain. Edited by J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith. Clarendon Press, Oxford.
26. West, M. 1993. Approximating posterior distributions by mixtures. J. R. Stat. Soc. B, 55: 409-422.
27. Wolpert, R.L. 1991. Monte Carlo integration in Bayesian statistical analysis. Contemp. Math. 115: 101-116.